Some works have attempted to tackle background clutter or similar object by applying context learning.
Background-aware CF (BACF) [1]} is proposed to extract more negative samples from the larger background by constructing a cropping matrix.
M. Mueller et al. [2]} managed to expand the receptive fields of filters by utilizing context information.
Although these methods are capable of sensing the surrounding environment, their excessive samples lack a reasonable attention mechanism.
Therefore, they are not able to employ the limited computational resources to the parts that may interfere with the tracked object.
